ML.NET is an open source, cross-platform, machine learning framework for .NET developers. ML.NET was originally developed in Microsoft Research and is now used across many products in Microsoft such as Windows, Bing, and PowerPoint. This talk introduces NimbusML, which brings the ML.NET library to Python. With NimbusML, developers familiar with the Scikit-learn API can start to take advantage of ML.NET performance just with few simple changes to their Scikit pipeline. The talk will also cover differentiators, such as NimbusML support for streaming datasets that don’t fit in memory, and featurizers/algorithms not easily available elsewhere.